Microwave spectrum analysis is often times an important capability in some research laboratories, production environments, telecommunications, and electronic warfare systems. Due to the relatively long wavelength of microwave signals (centimeter range), and due to the fact that it is challenging to fabricate high-quality on-chip inductors and filters at higher frequencies, it remains challenging to fabricate fast, power efficient, and high resolution spectrum analyzers in a compact size.
Various methods currently exist to perform spectrum analysis in either the time domain or the frequency domain. High-speed analog to digital converters (ADCs) are often used to perform time domain sampling of high-speed microwave signals. However, gigahertz-rate ADCs consume several watts of DC power and baseband computational complexity to perform time-frequency conversion (e.g., FFT) is typically order N log N. For this reason, analog Fourier transform circuits have been conceived to work directly on the time-domain signal, obviating the need for high-speed sampling and domain transformation processing. The input signal is converted from the time-domain to the frequency domain directly in the analog circuit via either dispersive structures, such as a non-uniform transmission line, or time delay correlators. Because the frequency resolution is proportional to the total time delay in these methods, structures tend to be very large due to the very high propagation velocity of electromagnetic waves. Typical media include spiraled non-uniform transmission lines or spools of fiber accompanied by electro-optic conversion and opto-electric conversion.
Alternative methods of performing spectral analysis, such as the pervasive spectrum analyzer, are in the frequency domain. Some benefits of frequency domain processing include high frequency resolution and large dynamic range, without the need for a high-speed sampling. However, spectrum analyzers typically requires a local oscillator operating at frequencies commensurate with the microwave signals of interest, a nonlinear down-converter (e.g., a mixer), and significant filtering at the RF and at intermediate frequencies. Because such a configuration yields very high frequency resolution and high dynamic range spectral analysis, the spectrum analyzer is a mainstay instrument in microwave laboratories. However, it consumes significant power and space. Previous chip-scale spectrum analyzers rely upon shrinking each of the components of their larger counterparts for realization in a monolithic integrated circuit. In these shrunken spectrum analyzers, the filter bank proves to be the most challenging component to miniaturize due to the lack of high-quality on-chip resonant structures. MEMS-based filter banks have been demonstrated to achieve high quality on-chip filtering; however they are subject to the shortcomings of MEMS-based technologies such as reliability and high bias voltages. Even without these MEMS-specific issues, the architecture of typical chip-scale spectrum analyzer consumes significant power, regardless of the filtering technology.
One weakness of time domain processing, such as sampling with high-speed ADCs and then performing time-frequency conversion in digital processing, is the high power and limited sample rate, thus limiting the maximum operating frequency of digital time-domain processing-based spectrum analyzers. Analog time-domain processing-based spectrum analyzers solve the problem of power and maximum operating frequency, but are often large in size. A weakness of frequency domain processing devices is their size and power (specifically the size of the filter banks). Even chip-scale spectrum analyzers, which have miniaturized the filter banks, suffer from high power requirements.